Senior Machine Learning Scientist
Senior Machine Learning Scientist
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Job Description
The Sr. ML Scientist will work with a team to conduct extraordinary research on data analytics and contribute to the longterm research agenda in largescale data analytics and machine learning as well as deliver innovative technologies and insights to Visas strategic products and business. This role represents a phenomenal chance to create key contributions to Visas strategic vision as a worldleading datadriven company. The successful candidate must have strong academic track record and demonstrate excellent software engineering skills. The successful candidate will be a selfstarter comfortable with ambiguity with strong attention to detail and excellent collaboration skills.
Our team is focusing on building a new product suite for Visas real time payments options! This will have a fraudmanagement focus and be scaled across many markets at Visa. This suite will also bring realtime fraud monitoring into play using the latest in Machine Learning & Deep Learning technologies. We are seeking ML Scientists that come from a wide array of backgrounds with the curiosity about creating something new and exciting for Visa.
Essential Functions
- Formulate business problems as technical data problems while ensuring key business drivers are collected in collaboration product stakeholders.
- Work with product engineering to ensure implementability of solutions. Deliver prototypes and production code based on need.
- Experiment with inhouse and thirdparty data sets to test hypotheses on relevance and value of data to business problems.
- Build needed data transformations on structured and unstructured data.
- Build and experiment with modeling and scoring algorithms. This includes development of custom algorithms as well as use of packaged tools based on machine learning analytics and statistical techniques.
- Devise and implement methods for adaptive learning with controls on efficiency methods for explaining model decisions where vital model validation A/B testing of models.
- Devise and implement methods for efficiently monitoring model efficiency and performance in production.
- Devise and implement methods for automation of all parts of the predictive pipeline to minimize labor in development and production.
- Contribute to development and adoption of shared predictive analytics infrastructure.
This is a hybrid position. Expectation of days in office will be confirmed by your Hiring Manager.
Qualifications :
Basic Qualifications
2 years of relevant work experience and a Bachelors degree OR 5 years of relevant work experience
Preferred Qualifications:
3 or more years of work experience with a Bachelors Degree or more than 2 years of work experience with an Advanced Degree (e.g. Masters MBA JD MD)
1 years of relevant experience with Masters in Computer Science Operations Research Statistics or highly quantitative field with strength in Deep Learning Machine Learning Data Analytics Statistical or other mathematical analysis OR 3 years of relevant work experience and a Bachelors degree
Relevant coursework in modeling techniques such as logistic regression Nave Bayes SVM decision trees or neural networks.
Ability to program in one or more scripting languages such as Perl or Python and one or more programming languages such as Java C or C#.
Experience with one or more common statistical tools such SAS R KNIME MATLAB.
Deep learning experience with TensorFlow is a plus.
Experience with Natural Language Processing is a plus.
Experience working with large datasets using tools like Hadoop MapReduce Pig or Hive is a plus.
Publications or presentation in recognized Machine Learning and Data Mining journals/conferences is a plus.
Additional Information :
Visa is an EEO Employer. Qualified applicants will receive consideration for employment without regard to race color religion sex national origin sexual orientation gender identity disability or protected veteran status. Visa will also consider for employment qualified applicants with criminal histories in a manner consistent with EEOC guidelines and applicable local law.
Remote Work :
No
Employment Type :
Fulltime
Employment Type
Full-time
